Pozify Exercise Router

--- license: other library_name: scikit-learn tags: - pose-estimation - exercise-recognition - video-classification - pozify datasets: - RickyRiccio/Real_Time_Exercise_Recognition_Dataset --- # Pozify Exercise Router This repository contains the Pozify exercise-router artifacts for classifying pose windows as `squat`, `push_up`, `shoulder_press`, or `unknown`. ## Model Details The active artifact is selected by `router_selection.json`. Current selected artifact: ```json { "selected_model": "temporal.pt", "selected_artifact": "temporal.pt", "reason": "prefer BiLSTM temporal when available; baseline falls back when temporal is missing" } ``` Artifacts: - `temporal.pt`: selected PyTorch BiLSTM temporal model trained over 30-frame feature tensors. - `router_selection.json`: active artifact selector used by Pozify runtime loading. - `router.joblib`: scikit-learn baseline artifact kept for comparison and fallback. - `training_report.md`: training and evaluation metrics. ## Intended Use The router is intended for Pozify's local app pipeline. It routes normalized pose sequences to the appropriate exercise-specific analyzer or rejects unsupported/uncertain clips as `unknown`. Supported labels: - `squat` - `push_up` - `shoulder_press` - `unknown` ## Training Data Primary source: - `RickyRiccio/Real_Time_Exercise_Recognition_Dataset` Unsupported classes from the source dataset, including curl variations, are mapped to `unknown`. Custom unknown clips can include idle standing, setup motion, stretching, partial reps, severe occlusion, and bad camera angles. ## Features The router uses 30-frame sliding windows with engineered pose features: - normalized landmarks - landmark visibility - knee, hip, elbow, and shoulder angles - relative distances such as hand width over shoulder width - frame deltas and velocities ## Evaluation The latest training report is included as `training_report.md`. Summary: | Model | Artifact | Accuracy | Unknown rejection rate | | --- | --- | ---: | ---: | | Baseline | `baseline.joblib` | 0.9987 | 0.9984 | | BiLSTM temporal | `temporal.pt` | 0.9964 | 0.9984 | ## Limitations - Metrics are based on the current router-window cache, not a broad deployment benchmark. - The router expects usable pose extraction and full-body framing where relevant. - Unsupported exercises are intentionally routed to `unknown`. - Addit...